automatic import of python-open-spiel

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diff --git a/.gitignore b/.gitignore
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--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/open_spiel-1.2.tar.gz
diff --git a/python-open-spiel.spec b/python-open-spiel.spec
new file mode 100644
index 0000000..e5a5f5a
--- /dev/null
+++ b/python-open-spiel.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-open-spiel
+Version:	1.2
+Release:	1
+Summary:	A Framework for Reinforcement Learning in Games
+License:	Apache 2.0
+URL:		https://github.com/deepmind/open_spiel
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/15/fa/b850c0b6c67643e12839deaa65a9775fcdd88eab747e0311e1a13aee0a89/open_spiel-1.2.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-pip
+Requires:	python3-attrs
+Requires:	python3-absl-py
+Requires:	python3-numpy
+Requires:	python3-scipy
+
+%description
+
+# OpenSpiel: A Framework for Reinforcement Learning in Games
+
+[![Documentation Status](https://readthedocs.org/projects/openspiel/badge/?version=latest)](https://openspiel.readthedocs.io/en/latest/?badge=latest)
+![build_and_test](https://github.com/deepmind/open_spiel/workflows/build_and_test/badge.svg)
+
+OpenSpiel is a collection of environments and algorithms for research in general
+reinforcement learning and search/planning in games. OpenSpiel supports n-player
+(single- and multi- agent) zero-sum, cooperative and general-sum, one-shot and
+sequential, strictly turn-taking and simultaneous-move, perfect and imperfect
+information games, as well as traditional multiagent environments such as
+(partially- and fully- observable) grid worlds and social dilemmas. OpenSpiel
+also includes tools to analyze learning dynamics and other common evaluation
+metrics. Games are represented as procedural extensive-form games, with some
+natural extensions. The core API and games are implemented in C++ and exposed to
+Python. Algorithms and tools are written both in C++ and Python.
+
+To try OpenSpiel in Google Colaboratory, please refer to `open_spiel/colabs` subdirectory or start [here](https://colab.research.google.com/github/deepmind/open_spiel/blob/master/open_spiel/colabs/install_open_spiel.ipynb).
+
+<p align="center">
+  <img src="docs/_static/OpenSpielB.png" alt="OpenSpiel visual asset">
+</p>
+
+# Index
+
+Please choose among the following options:
+
+*   [Installing OpenSpiel](docs/install.md)
+*   [Introduction to OpenSpiel](docs/intro.md)
+*   [API Overview and First Example](docs/concepts.md)
+*   [API Reference](docs/api_reference.md)
+*   [Overview of Implemented Games](docs/games.md)
+*   [Overview of Implemented Algorithms](docs/algorithms.md)
+*   [Developer Guide](docs/developer_guide.md)
+*   [Using OpenSpiel as a C++ Library](docs/library.md)
+*   [Guidelines and Contributing](docs/contributing.md)
+*   [Authors](docs/authors.md)
+
+For a longer introduction to the core concepts, formalisms, and terminology,
+including an overview of the algorithms and some results, please see
+[OpenSpiel: A Framework for Reinforcement Learning in Games](https://arxiv.org/abs/1908.09453).
+
+For an overview of OpenSpiel and example uses of the core API, please check out
+our tutorials:
+
+*   [Motivation, Core API, Brief Intro to Replictor Dynamics and Imperfect
+    Information Games](https://www.youtube.com/watch?v=8NCPqtPwlFQ) by Marc
+    Lanctot.
+    [(slides)](http://mlanctot.info/files/OpenSpiel_Tutorial_KU_Leuven_2022.pdf)
+    [(colab)](https://colab.research.google.com/github/deepmind/open_spiel/blob/master/open_spiel/colabs/OpenSpielTutorial.ipynb)
+*   [Motivation, Core API, Implementing CFR and REINFORCE on Kuhn poker, Leduc
+    poker, and Goofspiel](https://www.youtube.com/watch?v=o6JNHoGUXCo) by Edward
+    Lockhart.
+    [(slides)](http://mlanctot.info/files/open_spiel_tutorial-mar2021-comarl.pdf)
+    [(colab)](https://colab.research.google.com/github/deepmind/open_spiel/blob/master/open_spiel/colabs/CFR_and_REINFORCE.ipynb)
+
+If you use OpenSpiel in your research, please cite the paper using the following
+BibTeX:
+
+```bibtex
+@article{LanctotEtAl2019OpenSpiel,
+  title     = {{OpenSpiel}: A Framework for Reinforcement Learning in Games},
+  author    = {Marc Lanctot and Edward Lockhart and Jean-Baptiste Lespiau and
+               Vinicius Zambaldi and Satyaki Upadhyay and Julien P\'{e}rolat and
+               Sriram Srinivasan and Finbarr Timbers and Karl Tuyls and
+               Shayegan Omidshafiei and Daniel Hennes and Dustin Morrill and
+               Paul Muller and Timo Ewalds and Ryan Faulkner and J\'{a}nos Kram\'{a}r
+               and Bart De Vylder and Brennan Saeta and James Bradbury and David Ding
+               and Sebastian Borgeaud and Matthew Lai and Julian Schrittwieser and
+               Thomas Anthony and Edward Hughes and Ivo Danihelka and Jonah Ryan-Davis},
+  year      = {2019},
+  eprint    = {1908.09453},
+  archivePrefix = {arXiv},
+  primaryClass = {cs.LG},
+  journal   = {CoRR},
+  volume    = {abs/1908.09453},
+  url       = {http://arxiv.org/abs/1908.09453},
+}
+```
+
+## Versioning
+
+We use [Semantic Versioning](https://semver.org/).
+
+
+
+
+
+%package -n python3-open-spiel
+Summary:	A Framework for Reinforcement Learning in Games
+Provides:	python-open-spiel
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-open-spiel
+
+# OpenSpiel: A Framework for Reinforcement Learning in Games
+
+[![Documentation Status](https://readthedocs.org/projects/openspiel/badge/?version=latest)](https://openspiel.readthedocs.io/en/latest/?badge=latest)
+![build_and_test](https://github.com/deepmind/open_spiel/workflows/build_and_test/badge.svg)
+
+OpenSpiel is a collection of environments and algorithms for research in general
+reinforcement learning and search/planning in games. OpenSpiel supports n-player
+(single- and multi- agent) zero-sum, cooperative and general-sum, one-shot and
+sequential, strictly turn-taking and simultaneous-move, perfect and imperfect
+information games, as well as traditional multiagent environments such as
+(partially- and fully- observable) grid worlds and social dilemmas. OpenSpiel
+also includes tools to analyze learning dynamics and other common evaluation
+metrics. Games are represented as procedural extensive-form games, with some
+natural extensions. The core API and games are implemented in C++ and exposed to
+Python. Algorithms and tools are written both in C++ and Python.
+
+To try OpenSpiel in Google Colaboratory, please refer to `open_spiel/colabs` subdirectory or start [here](https://colab.research.google.com/github/deepmind/open_spiel/blob/master/open_spiel/colabs/install_open_spiel.ipynb).
+
+<p align="center">
+  <img src="docs/_static/OpenSpielB.png" alt="OpenSpiel visual asset">
+</p>
+
+# Index
+
+Please choose among the following options:
+
+*   [Installing OpenSpiel](docs/install.md)
+*   [Introduction to OpenSpiel](docs/intro.md)
+*   [API Overview and First Example](docs/concepts.md)
+*   [API Reference](docs/api_reference.md)
+*   [Overview of Implemented Games](docs/games.md)
+*   [Overview of Implemented Algorithms](docs/algorithms.md)
+*   [Developer Guide](docs/developer_guide.md)
+*   [Using OpenSpiel as a C++ Library](docs/library.md)
+*   [Guidelines and Contributing](docs/contributing.md)
+*   [Authors](docs/authors.md)
+
+For a longer introduction to the core concepts, formalisms, and terminology,
+including an overview of the algorithms and some results, please see
+[OpenSpiel: A Framework for Reinforcement Learning in Games](https://arxiv.org/abs/1908.09453).
+
+For an overview of OpenSpiel and example uses of the core API, please check out
+our tutorials:
+
+*   [Motivation, Core API, Brief Intro to Replictor Dynamics and Imperfect
+    Information Games](https://www.youtube.com/watch?v=8NCPqtPwlFQ) by Marc
+    Lanctot.
+    [(slides)](http://mlanctot.info/files/OpenSpiel_Tutorial_KU_Leuven_2022.pdf)
+    [(colab)](https://colab.research.google.com/github/deepmind/open_spiel/blob/master/open_spiel/colabs/OpenSpielTutorial.ipynb)
+*   [Motivation, Core API, Implementing CFR and REINFORCE on Kuhn poker, Leduc
+    poker, and Goofspiel](https://www.youtube.com/watch?v=o6JNHoGUXCo) by Edward
+    Lockhart.
+    [(slides)](http://mlanctot.info/files/open_spiel_tutorial-mar2021-comarl.pdf)
+    [(colab)](https://colab.research.google.com/github/deepmind/open_spiel/blob/master/open_spiel/colabs/CFR_and_REINFORCE.ipynb)
+
+If you use OpenSpiel in your research, please cite the paper using the following
+BibTeX:
+
+```bibtex
+@article{LanctotEtAl2019OpenSpiel,
+  title     = {{OpenSpiel}: A Framework for Reinforcement Learning in Games},
+  author    = {Marc Lanctot and Edward Lockhart and Jean-Baptiste Lespiau and
+               Vinicius Zambaldi and Satyaki Upadhyay and Julien P\'{e}rolat and
+               Sriram Srinivasan and Finbarr Timbers and Karl Tuyls and
+               Shayegan Omidshafiei and Daniel Hennes and Dustin Morrill and
+               Paul Muller and Timo Ewalds and Ryan Faulkner and J\'{a}nos Kram\'{a}r
+               and Bart De Vylder and Brennan Saeta and James Bradbury and David Ding
+               and Sebastian Borgeaud and Matthew Lai and Julian Schrittwieser and
+               Thomas Anthony and Edward Hughes and Ivo Danihelka and Jonah Ryan-Davis},
+  year      = {2019},
+  eprint    = {1908.09453},
+  archivePrefix = {arXiv},
+  primaryClass = {cs.LG},
+  journal   = {CoRR},
+  volume    = {abs/1908.09453},
+  url       = {http://arxiv.org/abs/1908.09453},
+}
+```
+
+## Versioning
+
+We use [Semantic Versioning](https://semver.org/).
+
+
+
+
+
+%package help
+Summary:	Development documents and examples for open-spiel
+Provides:	python3-open-spiel-doc
+%description help
+
+# OpenSpiel: A Framework for Reinforcement Learning in Games
+
+[![Documentation Status](https://readthedocs.org/projects/openspiel/badge/?version=latest)](https://openspiel.readthedocs.io/en/latest/?badge=latest)
+![build_and_test](https://github.com/deepmind/open_spiel/workflows/build_and_test/badge.svg)
+
+OpenSpiel is a collection of environments and algorithms for research in general
+reinforcement learning and search/planning in games. OpenSpiel supports n-player
+(single- and multi- agent) zero-sum, cooperative and general-sum, one-shot and
+sequential, strictly turn-taking and simultaneous-move, perfect and imperfect
+information games, as well as traditional multiagent environments such as
+(partially- and fully- observable) grid worlds and social dilemmas. OpenSpiel
+also includes tools to analyze learning dynamics and other common evaluation
+metrics. Games are represented as procedural extensive-form games, with some
+natural extensions. The core API and games are implemented in C++ and exposed to
+Python. Algorithms and tools are written both in C++ and Python.
+
+To try OpenSpiel in Google Colaboratory, please refer to `open_spiel/colabs` subdirectory or start [here](https://colab.research.google.com/github/deepmind/open_spiel/blob/master/open_spiel/colabs/install_open_spiel.ipynb).
+
+<p align="center">
+  <img src="docs/_static/OpenSpielB.png" alt="OpenSpiel visual asset">
+</p>
+
+# Index
+
+Please choose among the following options:
+
+*   [Installing OpenSpiel](docs/install.md)
+*   [Introduction to OpenSpiel](docs/intro.md)
+*   [API Overview and First Example](docs/concepts.md)
+*   [API Reference](docs/api_reference.md)
+*   [Overview of Implemented Games](docs/games.md)
+*   [Overview of Implemented Algorithms](docs/algorithms.md)
+*   [Developer Guide](docs/developer_guide.md)
+*   [Using OpenSpiel as a C++ Library](docs/library.md)
+*   [Guidelines and Contributing](docs/contributing.md)
+*   [Authors](docs/authors.md)
+
+For a longer introduction to the core concepts, formalisms, and terminology,
+including an overview of the algorithms and some results, please see
+[OpenSpiel: A Framework for Reinforcement Learning in Games](https://arxiv.org/abs/1908.09453).
+
+For an overview of OpenSpiel and example uses of the core API, please check out
+our tutorials:
+
+*   [Motivation, Core API, Brief Intro to Replictor Dynamics and Imperfect
+    Information Games](https://www.youtube.com/watch?v=8NCPqtPwlFQ) by Marc
+    Lanctot.
+    [(slides)](http://mlanctot.info/files/OpenSpiel_Tutorial_KU_Leuven_2022.pdf)
+    [(colab)](https://colab.research.google.com/github/deepmind/open_spiel/blob/master/open_spiel/colabs/OpenSpielTutorial.ipynb)
+*   [Motivation, Core API, Implementing CFR and REINFORCE on Kuhn poker, Leduc
+    poker, and Goofspiel](https://www.youtube.com/watch?v=o6JNHoGUXCo) by Edward
+    Lockhart.
+    [(slides)](http://mlanctot.info/files/open_spiel_tutorial-mar2021-comarl.pdf)
+    [(colab)](https://colab.research.google.com/github/deepmind/open_spiel/blob/master/open_spiel/colabs/CFR_and_REINFORCE.ipynb)
+
+If you use OpenSpiel in your research, please cite the paper using the following
+BibTeX:
+
+```bibtex
+@article{LanctotEtAl2019OpenSpiel,
+  title     = {{OpenSpiel}: A Framework for Reinforcement Learning in Games},
+  author    = {Marc Lanctot and Edward Lockhart and Jean-Baptiste Lespiau and
+               Vinicius Zambaldi and Satyaki Upadhyay and Julien P\'{e}rolat and
+               Sriram Srinivasan and Finbarr Timbers and Karl Tuyls and
+               Shayegan Omidshafiei and Daniel Hennes and Dustin Morrill and
+               Paul Muller and Timo Ewalds and Ryan Faulkner and J\'{a}nos Kram\'{a}r
+               and Bart De Vylder and Brennan Saeta and James Bradbury and David Ding
+               and Sebastian Borgeaud and Matthew Lai and Julian Schrittwieser and
+               Thomas Anthony and Edward Hughes and Ivo Danihelka and Jonah Ryan-Davis},
+  year      = {2019},
+  eprint    = {1908.09453},
+  archivePrefix = {arXiv},
+  primaryClass = {cs.LG},
+  journal   = {CoRR},
+  volume    = {abs/1908.09453},
+  url       = {http://arxiv.org/abs/1908.09453},
+}
+```
+
+## Versioning
+
+We use [Semantic Versioning](https://semver.org/).
+
+
+
+
+
+%prep
+%autosetup -n open-spiel-1.2
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-open-spiel -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 1.2-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..06f13d3
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+0a991c0c797a1bd646ba5f8725b5dcc3  open_spiel-1.2.tar.gz